Note that all of the readings are accessible from the original repositories I have linked to if you access them from the University (or use VPN ihrnto SCS if you are accessing from home).
| Week | Date | Topic | Speaker | Readings | Slides |
|---|---|---|---|---|---|
| 1 | 1/11 | Introduction to Disaggregated & Heterogeneous Platforms | M. Tamer Özsu | * R. Wang et al., The Case for Shared-Memory Databases with RDMA-Enabled Memory Disaggregation, Proc. VLDB Endowment, 2022. * I. Blagodurov et al., The time is ripe for disaggregated systems. Computer Architecture Today – ACM SIGARCH Blog, 2021. * S. Ghandeharizadeh et al., Disaggregated database management systems. In Performance Evaluation and Benchmarking, 2023. |
Slides |
| 2 | 1/18 | Introduction to Graph Processing | M. Tamer Özsu | * M. Besta et al., Demystifying Graph Databases: Analysis and Taxonomy of Data Organization, System Designs, and Graph Queries, ACM Comput. Surv. 56(2): 31:1-31:40, 2024. * M.T. Özsu and P. Valduriez, Big Data Processing. In Principles of Distributed Database Systems. Springer, 2022. (Focus on Section 10.4) * M.T. Özsu and P. Valduriez, Big Data Processing. In Principles of Distributed Database Systems. Springer, 2022. (Focus on Section 12.6) |
Slides |
| 3 | 1/25 | Networking infrastructure | Samer Al-Kiswany Ahmed Alquraan |
* R. Recio, A Tutorial of the RDMA Model, HPC Wire, 2006. * InfiniBand Trade Organization, Enabling the Modern Data Center – RDMA for the Enterprise, 2019. * A. Lerner et al., Databases on modern networks: A decade of research that now comes into practice. Proc. VLDB Endowment, 16(12):3894–3897, 2023. * D. Gouk et al., Direct access, High-Performance memory disaggregation with DirectCXL. In Proc. USENIX 2022 Annual Technical Conf., pages 287–294, 2022. |
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| 4 | 2/1 | Storage disaggregation | Lasantha Fernando Chanaka L. Lokupothagamage |
* A. Verbitski et al., Amazon Aurora: Design Considerations for High Throughput Cloud-Native Relational Databases, In Proc. ACM SIGMOD Int. Conf. Management of Data, pages 1041–1052, 2017. * P. Antonopoulos, et al., Socrates: The New SQL Server in the Cloud, In Proc. ACM SIGMOD Int. Conf. Management of Data, pages 1743–1756, 2019. |
Lasantha Slides Chanaka Slides |
| 5 | 2/8 | Storage disaggregation | Amin Setayesh Moni Haque |
* W. Cao et al., PolarFS: An Ultra-low Latency and Failure Resilient Distributed File System for Shared Storage Cloud Database, Proc. VLDB Endowment, 11(12): 1849-1962, 2018. * M. Vuppalapati et al., Building An Elastic Query Engine on Disaggregated Storage, In Proc. 17th USENIX Symp. on Networked Systems Design & Implementation, pages 449-462, 2020. |
Amin Slides Moni Slides |
| 6 | 2/15 | Storage/Memory disaggregation | Arman Davoodi Guanqi Huang |
* A. Agiwal et al., Napa: Powering Scalable Data Warehousing with Robust Query Performance at Google, 14(12): 2986-2998, 2021. * Y. Shan et al., LegoOS: A Disseminated, Distributed OS for Hardware Resource Disaggregation, In Proc. 14th USENIX Symp. on Operating System Design and Implementation, pages 69-87, 2018. |
Arman Slides Guanqi Slides |
| 7 | 2/22 | No class – Reading week | |||
| 8 | 2/29 | No class – I have a conflict | |||
| 9 | 3/7 | Memory disaggregation | Joseph Boulis Brian Song |
* Y. Zhang et al., Towards Cost-Effective and Elastic Cloud Database Deployment via Memory Disaggregation, Proc. VLDB Endowment, 14(10): 1900 - 1912, 2021. * Wei Cao et al., PolarDB Serverless: A Cloud Native Database for Disaggregated Data Centers, In Proc. ACM SIGMOD Int. Conf. Management of Data, pages 2477–2489, 2021. |
Joseph Slides Brian Slides |
| 10 | 3/12 | Hardware accelerators | Tilmann Rabl, Hasso Plattner Institute Xiangyao Yu, Uni. Wisconsin-Madison |
* C. Lutz et al., Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects, In Proc. ACM SIGMOD Int. Conf. Management of Data, pages 1633–1649, 2020. (This is the paper to review.) * T. Maltenberger et al, Evaluating Multi-GPU Sorting with Modern Interconnects, In Proc. ACM SIGMOD International Conference on Management of Data, , pages 1795–1809, 2022. * B. Yogatama et al, Orchestrating Data Placement and Query Execution in Heterogeneous CPU-GPU DBMS, Proc. VLDB Endowment_, 15(11): 2491-2503, 2022. (This is the paper to review.) A. Shanbhag et al, A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics, In Proc. ACM SIGMOD Int. Conf. Management of Data, pages 1617–1632, 2020. A. Shanbhag et al, Tile-based Lightweight Integer Compression in GPU, In Proc. ACM SIGMOD Int. Conf. Management of Data, pages 1390–1403, 2022. |
Tilmann Slides Tilmann video Xiangyao Slides Xiangyao video |
| 11 | 3/21 | Hardware accelerators | Gustavo Alonso, ETH Zürich Wolfgang Lehner & Alexander Krause, TU Dresden |
* D. Korilija et al, Farview: Disaggregated Memory with Operator Off-loading for Database Engines, In Proc. 12th Conf. on Innovative Data Syst. Research, 2022. (This is the paper to review) * Woods et al, Ibex - An Intelligent Storage Engine with Support for Advanced SQL Off-loading, Proc. VLDB Endow, 7(11): 963-974, 2014. * J. Pietrzyk et al., Program your (custom) SIMD instruction set on FPGA in C++, In Proc. 12th Conf. on Innovative Data Syst. Research, 2024. |
Gustavo Slides Wolfgang/Alexander Slides |
| 12 | 3/28 | Memory disaggregation | Sairaj Voruganti Philip Bernstein, Microsoft Research |
* Q. Zhang et al., Understanding the Effect of Data Center Resource Disaggregation on Production DBMSs, Proc. VLDB Endowment, 13(9): 1568-1581, 2020. * Q. Zhang et al., Redy: Remote Dynamic Memory Cache, Proc. VLDB Endowment, 15(4): 766 - 779, 2022. (This is the paper to review) * Q. Zhang et al., CompuCache: Remote Computable Caching using Spot VMs, In Proc. Conference on Innovative Data Systems Research, 2022 |
Sairaj Slides Phil Slides Phil Video |
| 13 | 4/4 | Project presentations | Arman Davoodi & Emanuel Haque Amin Setayesh & Sairaj Voruganti Lasantha Fernando & Chanaka L. Lokupothagamage Joseph Boulis, Brian Song & Guanqi Huang |
Triangle Listing for graphs stored on disaggregated memory Disaggregating Graph-based Vector Indexes Data Stream Processing on FaaS with Memory Disaggregation Elastic Memory Disaggregated System Architecture for Dynamic Workloads |
Slides Slides Slides Slides |